limbicnation
1069f6324d
- Fix .index() on numpy arrays in v3 individual face loop -> enumerate() - Remove dead classifier_type param from detect_faces() (cascade already selected via CascadeCache) - Change v1 RETURN_TYPES for face_metadata from IMAGE to FLOAT (is [B,6] bbox data, not image) - Improve v3 face_metadata tooltip: NOT an image warning - Remove unused import torch.nn.functional as F - Remove unused import StringInput - Replace _tensor_to_numpy() with _get_batch_dims() - removed dead img_np return
ComfyUI Face Detection Node
A ComfyUI custom node for face detection and cropping using OpenCV Haar cascades, with full ComfyUI v3 schema support and backward compatibility.
Features
- Face Detection: Uses OpenCV Haar cascade classifiers for robust face detection
- Flexible Cropping: Crop largest face or all detected faces
- Adjustable Parameters: Configurable detection threshold, minimum face size, and padding
- Multiple Classifiers: Choose between default and alternative Haar cascades
- ComfyUI v3 Ready: Full schema support with backward compatibility for v1/v2
- Async Execution: Stateless execution pattern for better performance
Installation
Via ComfyUI Manager (Recommended)
- Open ComfyUI Manager
- Search for "Face Detection Node"
- Click Install
Manual Installation
- Navigate to your ComfyUI custom nodes directory
- Clone this repository:
git clone https://github.com/Limbicnation/ComfyUI_FaceDetectionNode.git cd ComfyUI_FaceDetectionNode pip install -r requirements.txt
Usage
- Add the "Face Detection and Crop" node to your workflow
- Connect an image input
- Adjust parameters:
- Detection Threshold: Confidence threshold (0.1-1.0)
- Min Face Size: Minimum face size in pixels (32-512)
- Padding: Padding around detected faces (0-256)
- Output Mode: "largest_face" or "all_faces"
- Face Output Format: "strip" (horizontal layout) or "individual" (separate batch items)
- Classifier Type: "default" or "alternative"
Parameters
| Parameter | Type | Range | Default | Description |
|---|---|---|---|---|
| detection_threshold | Float | 0.1-1.0 | 0.8 | Face detection confidence threshold |
| min_face_size | Int | 32-512 | 64 | Minimum size for detected faces |
| padding | Int | 0-256 | 32 | Padding around detected faces |
| output_mode | Combo | - | largest_face | Output mode for detected faces |
| face_output_format | Combo | - | strip | Format for multiple faces (strip/individual) |
| classifier_type | Combo | - | default | Haar cascade classifier type |
Compatibility
- ComfyUI v3: Full schema support with async execution
- ComfyUI v1/v2: Backward compatibility via wrapper class
- Auto-detection: Automatically selects appropriate implementation
Requirements
- Python ≥ 3.8
- OpenCV ≥ 4.5.0
- PyTorch ≥ 1.9.0
- NumPy ≥ 1.21.0
- Pillow ≥ 8.0.0
License
Apache License Version 2.0, January 2004 - see LICENSE file for details.